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<p>Developing an autonomous multi-layer coupling model is of great significance for enhancing China’s independent support capability for the natural environment. Focusing on the newly developed Mass Conservation Ocean Model (MaCOM), this study constructs a fully autonomous global ocean-atmosphere coupled model based on the Yin-He Global Spectral Model (YHGSM) and the Community Coupler (C-Coupler). The coupled model effectively addresses the parallel control issue of independent I/O processes in the MaCOM model, thereby providing a methodological reference for the coupling control of other analogous numerical models. Experimental results show that the newly developed ocean-atmosphere coupled model achieves high parallel efficiency and reasonable forecast performance. In the simulation of Super Typhoon Hinnamnor (2022), it performs significantly better than the standalone atmospheric model in terms of intensity prediction.</p>

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Development of a global ocean-atmosphere coupled model based on the Mass Conservation Ocean Model

  • 期刊论文

  • 发表日期：

    2026年7月16日

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  • Yu Cao,
  • Jiagen Li,
  • Yan Chen,
  • Hao Ding,
  • Senliang Bao,
  • Bainian Liu,
  • Difu Sun,
  • Huizan Wang

摘要

Developing an autonomous multi-layer coupling model is of great significance for enhancing China’s independent support capability for the natural environment. Focusing on the newly developed Mass Conservation Ocean Model (MaCOM), this study constructs a fully autonomous global ocean-atmosphere coupled model based on the Yin-He Global Spectral Model (YHGSM) and the Community Coupler (C-Coupler). The coupled model effectively addresses the parallel control issue of independent I/O processes in the MaCOM model, thereby providing a methodological reference for the coupling control of other analogous numerical models. Experimental results show that the newly developed ocean-atmosphere coupled model achieves high parallel efficiency and reasonable forecast performance. In the simulation of Super Typhoon Hinnamnor (2022), it performs significantly better than the standalone atmospheric model in terms of intensity prediction.